Retrieval-augmented generation

Retrieval pipelines, vector search, chunking and reranking: how models are grounded in a corpus instead of their weights.

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arXiv AI

1d ago

SMA: Who Said That? Auditing Membership Leakage in Semi-Black-box RAG Controlling

arXiv:2508. 09105v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) and its Multimodal Retrieval-Augmented Generation (MRAG) significantly improve the knowledge coverage and contextual understanding of Large Language Models (LLMs) by introducing external knowledge sources.

By Shixuan Sun, Siyuan Liang, Jianjie Huang, Jingzhi Li, Xiaochun Cao

llms rag multimodal safety

arXiv AI

1d ago

Picking the Right Image to Classify: Reliable-Input Selection in Teledermatology

arXiv:2608. 16198v1 Announce Type: cross Abstract: Dermatology models face distribution shifts in teledermatology settings, where submitted images differ from the training data in lighting, angle, distance, focus, and framing.

By Fabian Gr\"oger, Marco Weishaupt, Philippe Gottfrois, Simone Lionetti, Linda Wermelinger, Nipun Ranasekara, Ludovic Amruthalingam, Alexander A. Navarini, Marc Pouly

rag benchmarks

arXiv AI

1d ago

Handoff-H1: An Orchestrated Vision-Agent System for Material Quantity Takeoff from Construction Blueprints

arXiv:2608. 15032v1 Announce Type: cross Abstract: Converting a set of architectural blueprints into a complete material quantity takeoff requires visual perception across drawing sheets, dimensional and multi-hop reasoning, and grounding in construction conventions that the drawings never state.

By Bruno Chicelli, Henrique Alves, Rodrigo Anselmo, Joshua Weinberg, Felipe Lemos, Jan Baryla

llms rag agents benchmarks

arXiv AI

1d ago

ATLAS: Scaffold-Free Algorithm Synthesis by LLMs via Embedding-Guided Quality-Diversity Search

arXiv:2608. 15546v1 Announce Type: new Abstract: Most LLM-based automated algorithm design methods optimize a designated component within a human-specified scaffold, fixing overall organization and component interactions.

By Danial Yazdani, Mohammad Nabi Omidvar, Yuan Sun, Maksud Ibrahimov, Xiaodong Li

llms rag benchmarks

arXiv AI

1d ago

Stop Indexing at Full Precision: Revisiting Clustering for Vector Embeddings

arXiv:2608. 14648v1 Announce Type: cross Abstract: In this study, we revisit three widely used techniques in vector search and utilize them to optimize vector embedding indexing through clustering: dimensionality reduction, quantization, and dimension pruning.

By Leonardo Kuffo, Peter Boncz

rag efficiency

arXiv AI

1d ago

Decoupled Temporal Encoding for Generative Recommendation

arXiv:2608. 16274v1 Announce Type: cross Abstract: Positional encoding is a fundamental component of Transformer-based generative recommendation models, where user histories are modeled as autoregressive item sequences.

By Pengfei Jia, Jingjian Wang, Jingmao Li, Ge Zhang, Feng Shi

llms rag nlp safety

arXiv AI

1d ago

Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening

arXiv:2608. 14763v1 Announce Type: cross Abstract: Assessment of ventriculomegaly (VM) on fetal brain ultrasound relies primarily on measuring lateral ventricular atrial width on standard planes, which is operator-dependent and may not fully reflect the overall ventricular enlargement.

By Yuhao Huang, Yuanji Zhang, Yuhuan Lu, Dong Ni, P. Ellen Grant, Davood Karimi

llms rag multimodal benchmarks safety

arXiv AI

1d ago

Noesis: Bidirectional Graph-RAG with Adaptive Parallelism and Cross-Knowledge-Base Semantic Discovery

arXiv:2608. 15919v1 Announce Type: cross Abstract: Retrieval-Augmented Generation over knowledge graphs (Graph-RAG) has emerged as a powerful paradigm for grounding large language models in domain-specific corpora.

By Nicola Cogotti

llms rag efficiency

arXiv AI

1d ago

Catching Hallucinated Citations in Video-LLM Question Answering: A Self-Verification Pipeline and Verifier Ablation Study

arXiv:2608. 15574v1 Announce Type: cross Abstract: Video question answering systems built on vision-language models often produce timestamped claims with high confidence even when unsupported by the cited frame.

By Yogesh Kumar

llms rag nlp multimodal benchmarks safety

arXiv Machine Learning

1d ago

DUET: Dual-Teacher On-Policy Distillation via Same-Weight Disagreement for Prohibition Compliance

arXiv:2608. 14644v1 Announce Type: new Abstract: Real-world LLM deployments increasingly rely on runtime-injected prohibitions--enterprise policies, PII redlines, tool boundaries--that vary per request and per tenant.

By Zihan Li, Feifei Li, Wenhui Que

llms rag reinforcement-learning fine-tuning efficiency benchmarks safety

arXiv AI

1d ago

MELD: A Protocol for Merging Knowledge Across Distributed Agentic Memories

arXiv:2608. 16357v1 Announce Type: cross Abstract: Autonomous agents share a transport and can call each other's tools, but they cannot share what they know: no protocol lets two agents' memories reconcile a fact phrased two ways, link related facts held apart, or reconcile contradictory knowledge without silently discarding either claim.

By Lauri Lov\'en, Jaakko Sauvola, Jukka Riekki, Sasu Tarkoma

rag agents

arXiv AI

1d ago

ETHOS: Towards a Modular Ethics Framework for Clinical Multi-Agent Systems

arXiv:2608. 15424v1 Announce Type: cross Abstract: The rapid adoption of large language models has enabled the development of clinical multi-agent systems (MAS) capable of integrating multimodal patient data and supporting increasingly complex clinical decision-making.

By Rakesh Sharma, Sydney Pugh, Cameron Beeche, Pankhuri Singhal, Rachel Wu, Margaret Eby, Jeffrey Duda, James Gee, Kyra O'Brien, Hersh Sagreiya, Marina Serper, Victoria Gershuni, Angela Bradbury, Anurag Verma, Eric Eaton, Kevin B. Johnson, Walter Witschey

llms rag agents multimodal safety

arXiv AI

1d ago

Prompting is not enough: supervised baselines and leakage control for measuring shared decision-making with LLMs in pediatric encounters

arXiv:2608. 14792v1 Announce Type: cross Abstract: Objectives: To determine whether zero-shot prompting of a large language model (LLM) is sufficient to detect shared decision-making (SDM) behaviors in real clinical encounters, and whether supervised learning adds value under patient-grouped, nested evaluation.

By Bernardo Modenesi, Jody Lin, Kimberly Kaphingst, Angela Zhu, Maya Wheeler, Peilu Zhang, Angela Fagerlin

llms rag

arXiv AI

1d ago

Topological Attribution Distance (TAD): Revealing Segment-Level RAG Influence on LLM Output Geometry for Incident Log Analysis

arXiv:2608. 16775v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed in cybersecurity operations to assist cybersecurity analysts with rapid decision-making against emerging threats.

By Reza Fayyazi, Michael Zuzak, Shanchieh Jay Yang

llms rag agents benchmarks

arXiv AI

1d ago

OGX: An Open-Source, Vendor-Neutral Generative AI Application Server

arXiv:2608. 14580v1 Announce Type: new Abstract: OGX (Open GenAI Stack) is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Google) with pluggable backend providers.

By Francisco Javier Arceo, S\'ebastien Han, Matthew Farrellee, Charlie Doern, Yuan Tang, Derek Higgins, Varsha Prasad Narsing, Gordon Sim, Sumanth Kamenani, Ben Browning, Raghotham Murthy

llms rag agents safety

arXiv Machine Learning

1d ago

Every Expert Counts: ExactMoE for Memory-Efficient W4A16 Inference

arXiv:2608. 15383v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) language models reduce arithmetic by activating only a small subset of experts per token, yet deployment still requires storing and moving the full expert bank.

By Amjad Saab

llms rag efficiency benchmarks

arXiv Machine Learning

1d ago

A Unified Geometric Framework for Developmental Analysis of Spatial Transcriptomic Data

arXiv:2608. 15306v1 Announce Type: cross Abstract: High-throughput single-cell and spatial transcriptomic technologies provide high-resolution snapshots of heterogeneous cellular states, but their destructive nature prevents repeated measurements of the same cells over time.

By Mary Chriselda Antony Oliver, Kaitlyn Hohmeier, Tuyen Tran, Alejandra Castillo, Caroline Moosm\"uller, Shiying Li

rag efficiency

arXiv Machine Learning

1d ago

NeuRoute: Logit-Guided Neural Routing for Billion-Scale Vector Search with Sub-Hour Index Construction

arXiv:2608. 15438v1 Announce Type: cross Abstract: Building approximate nearest neighbor (ANN) indexes at billion scale is often dominated by expensive global clustering or graph construction, making time-to-index a first-order systems concern.

By Xingqiao Wang, Zi Wang, Xiaowei Xu

rag efficiency benchmarks

arXiv AI

1d ago

An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

arXiv:2605. 13221v2 Announce Type: replace Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC).

By Hanwen Zhang, Dusit Niyato, Wei Zhang, Xin Lou, Malcolm Yoke Hean Low

llms rag agents reinforcement-learning

arXiv AI

1d ago

TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability

arXiv:2405. 17678v2 Announce Type: replace-cross Abstract: Achieving zero-shot adversarial robustness without sacrificing generalization remains challenging for foundation models such as CLIP, especially under large adversarial perturbations.

By Fengji Ma, Hei Victor Cheng, Chenxing Li, Li Liu

rag safety